Search results for: robust regression

Authors: Brianna Z. Ross, Jonathan N. Livingston

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Given that discussions of racism and racial tensions have become more salient, there is a need to evaluate the impacts of racialization among Black individuals. Racial discrimination has become one of the most common experiences within the Black American population. Likewise, Black individuals have indicated a need to address their racial identities at an earlier age than their non-Black peers. Further, Black individuals have been found at the forefront of multiple social and political movements, including but not limited to the Civil Rights Movement, Black Lives Matter, MeToo, and Say Her Name. Moreover, the present study sought to explore the predictive relationships that exist between racial discrimination, racial identity, and activism in the Black community. The results of standard and hierarchical regression analyses revealed that racial discrimination and racial identity significantly predict each other, but only racial discrimination is a significant predictor for the relationship to activism. Nonetheless, the results from this study will provide a basis for social scientists to better understand the impacts of racialization on the Black American population.

Keywords: activism, racialization, racial discrimination, racial identity

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Authors: Philip Edinger, Christian Ludwig

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The formation and control of tars remain one of the major challenges in the implementation of biomass gasification technologies. Robust, on-line analytical methods are needed to investigate the fate of tar compounds when different measures for their reduction are applied. This work establishes an on-line UV-Vis method, based on a liquid quench sampling system, to monitor tar compounds in biomass gasification processes. Recorded spectra from the liquid phase were analyzed for their tar composition by means of a classical least squares (CLS) and partial least squares (PLS) approach. This allowed for the detection of UV-Vis active tar compounds with detection limits in the low part per million by volume (ppmV) region. The developed method was then applied to two case studies. The first involved a lab-scale reactor, intended to investigate the decomposition of a limited number of tar compounds across a catalyst. The second study involved a gas scrubber as part of a pilot scale wood gasification plant. Tar compound quantification results showed good agreement with off-line based reference methods (GC-FID) when the complexity of tar composition was limited. The two case studies show that the developed method can provide rapid, qualitative information on the tar composition for the purpose of process monitoring. In cases with a limited number of tar species, quantitative information about the individual tar compound concentrations provides an additional benefit of the analytical method.

Keywords: biomass gasification, on-line, tar, UV-Vis

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Authors: Yangchun Xiong

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The goal of this study is to demonstrate the impact of the changing importance of technology skill under the evolution of artificial intelligence on the job requirements for accountants. The analysis is based on data from the Chinese employment market from 2012 to 2022 under different educational backgrounds. The research objectives are achieved through multiple regression and relative importance analysis. The analysis indicates that the changing importance of technology skills have significant effects on the job requirements of accountants. Trends show that from 2012 to 2022, the relative importance of technology skills decreased. However, this trend was reversed in 2020. Differences exist in both overall characteristics and trend features for job seekers with different educational backgrounds. The research findings provide insights for recommendations on how job seekers and educational institutions should take actions in the context of AI to promote employment and personal development.

Keywords: Artificial intelligence, Accountant, Educational background, Technology skills, Job requirements

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Authors: Shubham Dwivedi, Raghavender Medishetti, Rita Rani, Aarti Sevilimedu, Pushkar Kulkarni, Yogeeswari Perumal

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Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder of early onset, characterized by impaired sociability, cognitive function and stereotypies. There is a significant urge to develop and establish new animal models with ASD-like characteristics for better understanding of underlying mechanisms. The aim of the present study was to develop a cost and time effective zebrafish model with quantifiable parameters to facilitate mechanistic studies as well as high-throughput screening of new molecules for autism. Zebrafish embryos were treated with valproic acid and a battery of behavioral tests (anxiety, inattentive behavior, irritability and social impairment) was performed on larvae at 7th day post fertilization, followed by study of molecular markers of autism. This model shows a significant behavioural impairment in valproic acid treated larvae in comparison to control which was again supported by alteration in few marker genes and proteins of autism. The model also shows a rescue of behavioural despair with positive control drugs. The model shows robust parameters to study behavior, molecular mechanism and drug screening approach in a single frame. Thus we postulate that our 7 days zebrafish larval model for autism can help in high throughput screening of new molecules on autism.

Keywords: autism, zebrafish, valproic acid, neurodevelopment, behavioral assay

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Authors: Sourour Chaabane, Davide Clematis, Marco Panizza

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This study investigates the oxidation of Erythrosine B (EB) food dye by a homogeneous electro-Fenton process using iron (II) sulfate heptahydrate as a catalyst, carbon felt as cathode, and Ti/RuO2. The treated synthetic wastewater contains 100 mg L⁻¹ of EB and has a pH = 3. The effects of three independent variables have been considered for process optimization, such as applied current intensity (0.1 – 0.5 A), iron concentration (1 – 10 mM), and stirring rate (100 – 1000 rpm). Their interactions were investigated considering response surface methodology (RSM) based on Doehlert design as optimization method. EB removal efficiency and energy consumption were considered model responses after 30 minutes of electrolysis. Analysis of variance (ANOVA) revealed that the quadratic model was adequately fitted to the experimental data with R² (0.9819), adj-R² (0.9276) and low Fisher probability (< 0.0181) for EB removal model, and R² (0.9968), adj-R² (0.9872) and low Fisher probability (< 0.0014) relative to the energy consumption model reflected a robust statistical significance. The energy consumption model significantly depends on current density, as expected. The foregoing results obtained by RSM led to the following optimal conditions for EB degradation: current intensity of 0.2 A, iron concentration of 9.397 mM, and stirring rate of 500 rpm, which gave a maximum decolorization rate of 98.15 % with a minimum energy consumption of 0.74 kWh m⁻³ at 30 min of electrolysis.

Keywords: electrofenton, erythrosineb, dye, response serface methdology, carbon felt

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Authors: Mary Okonkwo Ekwy

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The problem of the growing disillusionment of College of Education teachers with academic life vis-à-vis their job satisfaction and commitment was investigated in this study with a view to finding out if both their job satisfaction and commitment have suffered, and to find out if there was a relationship between job satisfaction and commitment among these College of Education teachers. Due consideration was also given in the study to the possible effects of demographic variables on attitudes to their job. To carry out a study of job satisfaction and commitment among the College of Education teachers and to explore the relationship between them, research instruments were used for measuring the levels of job satisfaction and commitment among them. A sample of 200 Colleges of Education teachers, comprising 15 Professors, 9 Principal Lecturers, 70 Senior Lecturer and 106 Lecturers was used for the study. Five major hypothesis were tested with regard to the relationship between job satisfaction and commitment among the teachers. The Pearson correlation, the F-ratio, and regression analysis were used for data analysis and hypothesis testing. The result of this investigation suggests that, perhaps the best way to secure the commitment of teachers is to ensure their job satisfaction. Future investigations will further enrich our knowledge about these very important themes.

Keywords: job satisfaction, commitment, academic staff, college of education

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Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

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One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: active transport, public transport accessibility, walkability, ordered logit model

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Authors: Syed Atif Ali, Farzan Yahya

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This research paper covers the issue of risk management impact on the company performance. Degree of financial leverage (DFL), degree of operating leverage (DOL) and the working capital ratio (WCR) are taken as independent variables which are the representative of risk and the earning price per share (EPS), return on assets (ROA), return on equity (ROE), Sales and Net profits which are the representative of performance. Last 10 years (2004-2013) of Cement sector of Pakistan data is chosen as sample for analyze their relations by multiple regression technique. Through analyses, it is found that WCR impact adequately on the company performance because if company has enough liquidity than it perform its operations smoothly and enhance its performance very well. DFL should be control moderately because enough DFL leads performance of company downward. On the other hand, the DOL should be less because it causes the less profitability for a company from its operations.

Keywords: degree of financial leverage (DFL), degree of operating leverage (DOL), working capital ratio (WCR), earning per share (EPS), return on equity (ROE), return on assets (ROA)

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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Authors: Golamhassan Ghahramani Aghdam, Pedram Bavili Tabrizi

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The aim of this research is to investigate the relationship between accounting information and the value of the companies accepted in Tehran Exchange Market. The dependent variable in this research is the value of a company that is measured by price coefficients, and the independent variables are balance sheet information, profit and loss information, cash flow state information, and profit quality characteristics. The profit quality characteristic index is to be related and to be on-time. This research is an application research, and the research population includes all companies that are active in Tehran exchange market. The number of 194 companies was selected by the systematic method as the statistics sample in the period of 2018-2019. The multi-variable linear regression model was used for the hypotheses test. The results show that there is no relationship between accounting information and companies’ value (stock value) that can be due to the lack of efficiency of the investment market and the inability to use the accounting information by investment market activists.

Keywords: accounting information, company value, profit quality characteristics, price coefficient

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Authors: Jee-Sang Kim, Jong Ho Park

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Geopolymer concretes are a new class of construction materials that have emerged as an alternative to Ordinary Portland cement concrete. Considerable researches have been carried out on material development of geopolymer concrete, however, a few studies have been reported on the structural use of them. This paper presents the bond behaviors of reinforcement embedded in fly ash based geopolymer concrete. The development lengths of reinforcement for various compressive strengths of concrete, 20, 30 and 40 MPa, and reinforcement diameters, 10, 16, and 25 mm are investigated. Total 27 specimens were manufactured and pull-out test according to EN 10080 was applied to measure bond strength and slips between concrete and reinforcements. The average bond strengths decreased from 23.06MPa to 17.26 MPa, as the diameters of reinforcements increased from 10mm to 25mm. The compressive strength levels of geopolymer concrete showed no significant influence on bond strengths in this study. Also, the bond-slip relations between geopolymer concrete and reinforcement are derived using non-linear regression analysis for various experimental conditions.

Keywords: bond-slip relation, bond strength, geopolymer concrete, pull-out test

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Authors: Gebreegziabher Hailu

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This paper presents the development of residual power series methods aimed at efficiently solving stiff differential equations, which pose significant challenges in numerical analysis due to their rapid changes in solution behavior. The RPSM is a numerical approach that generates polynomial-based approximate solutions without the need for linearization, discretization, or perturbation techniques, making it straightforward to implement and less prone to computational errors. We introduce an approach that utilizes power series expansions combined with residual minimization techniques to enhance convergence and stability. By analyzing the theoretical foundations of stiffness, we delve into the formulation of the residual power series method, detailing how it effectively captures the dynamics of stiff systems while maintaining computational efficiency. Numerical experiments demonstrate the method's superiority in terms of accuracy and computational cost when compared to traditional methods like implicit Runge-Kutta or multistep techniques. We also explore adaptive strategies within our framework to automatically adjust parameters based on the stiffness characteristics of the problem at hand. Ultimately, our findings contribute to the broader toolkit for tackling stiff differential equations, offering a robust alternative that promises to streamline computational workflows in various applied mathematics and engineering contexts.

Keywords: residual power series methods, stiff differential equoations, numerical approach, Runge Kutta methods

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Naveed Ul Hassan, Bilal Aziz, Maryam Mushtaq, Imran Ameen Khan

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Equity risk premium (ERP) is the stock return in excess of risk free return. Even though it is an essential topic of finance but still there is no common consensus upon its forecasting. For forecasting ERP, apart from the macroeconomic variables attention is devoted to technical indicators as well. For this purpose, set of 14 technical and 14 macro-economic variables is selected and all forecasts are generated based on a standard predictive regression framework, where ERP is regressed on a constant and a lag of a macroeconomic variable or technical indicator. The comparative results showed that technical indicators provide better indications about ERP estimates as compared to macro-economic variables. The relative strength of ERP predictability is also investigated by using National Bureau of Economic Research (NBER) data of business cycle expansion and recessions and found that ERP predictability is more than twice for recessions as compared to expansions.

Keywords: equity risk premium, forecasting, macroeconomic indicators, technical indicators

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Authors: Muhammad Naeem, Abdus Salam, Sumera Yasmin, Abir Ishtiaq

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In the present study, eighty-three wild Oreochromis aureus of different body size ranging 5.3-14.6 cm in total length were collected from the River Chenab, District Muzzafer Garh, Pakistan to investigate the parameters of length –weight, length-length relationships and condition factor in relation to size. Each fish was measured and weighed on arrival at laboratory. Log transformed regressions were used to test the allometric growth. Length-weight relationship was found highly significant (r = 0.964; P < 0.01). The values of exponent “ b” in Length–weight regression (W=aL^b), deviated from 3, showing isometric growth (b = 2.75). Results for LLRs indicated that these are highly correlated (P < 0.001). Condition factor (K) found constant with increasing body weight, however, showed negative influence with increasing total length.

Keywords: lenght-weight, Oreochromis aureus, morphometric study

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Authors: Somchai Buaroong

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This research aims to investigating strong points and challenges in application of an online learning management system to an English course. Data were collected from observation, learners’ oral and written reports, and the teacher’s journals. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The findings show that the system was an additional channel to enhance English language learning through written class assignments that were digitally accessible by any group members, and through communication between the teacher and learners and among learners themselves. Thus, the learning management system could be a promising tool for foreign language teachers. Also revealed in the study were difficulties in its use. The article ends with discussions of findings of the system for foreign language classes in association to pedagogy are also included and in the level of signification.

Keywords: english course, foreign language system, online learning management system, teacher’s journals

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Authors: Evy Rombaut, Marie-Anne Guerry

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Predicting voluntary turnover of employees is an important topic of study, both in academia and industry. Researchers try to uncover determinants for a broader understanding and possible prevention of turnover. In the current study, we use a data set based approach to reveal determinants for turnover, differing for blue and white collar workers. Our data set based approach made it possible to study actual turnover for more than 500000 employees in 15692 Belgian corporations. We use logistic regression to calculate individual turnover probabilities and test the goodness of our model with the AUC (area under the ROC-curve) method. The results of the study confirm the relationship of known determinants to employee turnover such as age, seniority, pay and work distance. In addition, the study unravels unknown and verifies known differences between blue and white collar workers. It shows opposite relationships to turnover for gender, marital status, the number of children, nationality, and pay.

Keywords: employee turnover, blue collar, white collar, dataset analysis

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Authors: E. Lacasa, J. L. Santolaya, I. Millán

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The progress toward sustainability implies maintaining and preferably improving both, human and ecosystem well-being, according to a triple bottom line that includes the environmental, economic and social dimensions. The life cycle assessment (LCA) is a method applicable to all production sectors that aims to quantify the environmental pressures and the benefits related to goods and services, as well as the trade-offs and the scope for improving areas of the production process. While using LCA to measure the environmental dimension of sustainability is widespread, similar approaches for the economic and the social dimensions still have limited application worldwide and there is a need for consistent and robust methods and indicators. This paper focuses on the milk production process and presents the analysis of the flows exchanged by an industrial installation through accounting all the energy and material inputs and the associated emissions and waste outputs at this stage of its life cycle. The functional unit is one litre of milk produced. Different metrics and indicators are used to assess the three dimensions of sustainability. Metrics considered useful to assess the production activities are the total water and energy consumptions and the milk production volume of each cow. The global warming, the value added and the working hours are indicators used to measure each sustainability dimension. The study is performed with two types of feeding of the cows, which includes a change in percentages of components as well. Nutritional composition of the milk obtained is almost kept. It is observed that environmental and social improvements involve high economic costs.

Keywords: milk production, sustainability, indicators, life cycle assessment

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

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In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Megan E. Davies

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With the intention of identifying cognitive processes uniquely involved in the dark triad personality traits of psychopathy, Machiavellianism, and narcissism, this study aimed to determine further potential differences and parameters of individual traits by explaining a statistically significant amount of variance between the constructs of manipulativeness, impulsiveness, grit, and need for cognition within the dark triad. Applying a cross-sectional design, N = 96 participants self-reported using the MACH-IV, SRP-III, NFC-S, and Grit Scale for Perseverance and Passion for Long-Term Goals. Hierarchical regression analyses showed that only manipulativeness predicted Machiavellianism, whereas manipulativeness and impulsiveness were found to have predictive qualities for psychopathy. Overall, these results found areas of discrepancy and overlap between manipulation and impulsivity regarding psychopathy and Machiavellianism. Additionally, this study serves to preliminarily eliminate the Need for Cognition and grit as predictive variables for Machiavellianism and psychopathy.

Keywords: Machiavellianism, psychopathy, manipulation, impulsiveness, need for cognition, grit, dark triad

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: Gelila Tamyalew, Asres Abitie

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Community Pharmacists (CPs) have a significant part in consumer choice in the rational use of LMPPs. The opinion of pharmacists regarding branded and generic medications can offer a perception of the potential obstacles that might have to be overcome to advance generic medicine utilization. Many factors affect CPs' attitudes negatively toward LMPPs. Therefore, the current study assessed factors that can affect CPs' attitudes toward LMPPs. In the regression analysis of variables, three variables were associated with CPs' attitudes toward LMPPs. These are; maximum educational status, professional status, and year of experience in community pharmacy practice. Moreover, lack of belief in LMPPs, substitution agreement with the prescriber, cost-effectiveness of LMPPs, and consumer preference/demand were the most influencing reasons for the selection of LMPPs. In conclusion, the attitude of CPs seems suboptimal that requires an intervention to optimize LMPP utilization.

Keywords: locally manufactured pharmaceutical products, attitude, community pharmacist, Ethiopia

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Authors: Hui-Yu Peng, Hsiu-I Hsueh, Li-Ming Chen

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Most studies focused on bullying behaviors among students, however few research concerns about teachers’ bullying behaviors against students. In order to have more understandings and reduce teacher bullying, it is important to examine what factors may affect teachers’ bullying behaviors. This study aimed to explore the connections between different psychological variables and teacher bullying. Four variables, neuroticism, extraversion, teacher-student relationship, and belief in a just world for others (BJW-others), were selected in this study. Four hundred and five elementary and secondary school teachers in Taiwan endorsed the self-reported surveys. Multiple regression method was used to analyze data. Results revealed that teachers’ BJW-others and extraversion did not have significant correlations with teacher bullying scores. However, closed teacher-student relationship and neuroticism can negatively and positively predict teachers’ bullying behaviors against students, respectively. Implications for preventing teacher bullying were discussed at the end of this study.

Keywords: belief in a just world for others, big five personality traits, teacher bullying, teacher-student relationship

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Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: Chander Shekhar, Jeetendra Yadav, Shaziya Allarakha

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Hypertension has been described as an 'iceberg disease' as those who suffered are ignored and hence usually seek healthcare services at a very late stage. It is estimated that more than 2 million Indians are suffering from hypertensive heart disease that contributed to above 0.13 million deaths in 2016. The paper study aims to know the prevalence of Hypertension in India and its variation by socioeconomic backgrounds and to find out risk factors discriminating hypertension with special emphasis on consumption of tobacco and alcohol among men aged 15-54 years in India. The paper uses NFHS (2015-16) data. The paper used binary logistic regression and discriminant analysis to find significant predictors and discriminants of interest. The prevalence of hypertension was 16.5% in the study population. The results suggest that consumption of alcohol and tobacco are significant discriminant characteristics in carrying hypertension irrespective of what socioeconomic background characteristic he possesses.

Keywords: hypertention, alcohol, tobacco, discriminant

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Authors: Lauren Provost

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The digital world remains increasingly vulnerable, making the development of effective cybersecurity approaches even more critical in supporting the success of the digital economy and national security. Although approaches to cybersecurity have shifted and improved in the last decade with new models, especially with cloud computing and mobility, a record number of high severity vulnerabilities were recorded in the National Institute of Standards and Technology (NIST), and its National Vulnerability Database (NVD) in 2020. This is due, in part, to the increasing complexity of cyber ecosystems. Security must be approached with a more comprehensive, multi-tool strategy that addresses the complexity of cyber ecosystems, including the human factor. Ethical hacking has emerged as such an approach: a more effective, multi-strategy, comprehensive approach to cyber security's most pressing needs, especially understanding the human factor. Research on ethical hacking, however, is limited in scope. The two main objectives of this work are to (1) provide highlights of case studies in ethical hacking, (2) provide a conceptual framework for research in ethical hacking that embraces and addresses both technical and nontechnical security measures. Recommendations include an improved conceptual framework for research centered on ethical hacking that addresses many factors and attributes of significant attacks that threaten computer security; a more robust, integrative multi-layered framework embracing the complexity of cybersecurity ecosystems.

Keywords: ethical hacking, literature review, penetration testing, social engineering

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Authors: Rouzbeh Ramezani, Renzo Di Felice

Abstract:

Nowadays, removal of CO₂ as one of the major contributors to global warming using alternative solvents with high CO₂ absorption efficiency, is an important industrial operation. In this study, three amines, including 2-methylpiperazine, potassium sarcosinate and potassium lysinate as potential additives, were added to the potassium carbonate solution as a base solvent for CO₂ capture. In order to study the absorption performance of CO₂ in terms of loading capacity of CO₂ and absorption rate, the absorption experiments in a blend of additives with potassium carbonate were carried out using the vapor-liquid equilibrium apparatus at a temperature of 313.15 K, CO₂ partial pressures ranging from 0 to 50 kPa and at mole fractions 0.2, 0.3, and 0.4. Furthermore, the performance of CO₂ absorption in these blend solutions was compared with pure monoethanolamine and with pure potassium carbonate. Finally, a correlation with good accuracy was developed using the nonlinear regression analysis in order to predict CO₂ loading capacity.

Keywords: absorption rate, carbon dioxide, CO2 capture, global warming, loading capacity

Procedia PDF Downloads 288

Authors: Muhammad Mohsin, Fawad Ahmad, Fatima Batool, Muhammad Kaab Zarrar

Abstract:

The integration of the Internet of Things (IoT) and edge computing devices offers a transformative approach to electronic waste management, particularly in the dismantling of printed circuit boards (PCBs). This paper explores how these technologies optimize operational efficiency and improve environmental sustainability by addressing challenges such as data security, interoperability, scalability, and real-time data processing. Proposed solutions include advanced machine learning algorithms for predictive maintenance, robust encryption protocols, and scalable architectures that incorporate edge computing. Case studies from leading e-waste management facilities illustrate benefits such as improved material recovery efficiency, reduced environmental impact, improved worker safety, and optimized resource utilization. The findings highlight the potential of IoT and edge computing to revolutionize e-waste dismantling and make the case for a collaborative approach between policymakers, waste management professionals, and technology developers. This research provides important insights into the use of IoT and edge computing to make significant progress in the sustainable management of electronic waste

Keywords: internet of Things, edge computing, waste PCB disassembly, electronic waste management, data security, interoperability, machine learning, predictive maintenance, sustainable development

Procedia PDF Downloads 38

Authors: Aisha Bano, Rizwan Nazir

Abstract:

The present study aimed at exploring the impact of meaning in life on psychological well-being and stress among university students. Victor Frankl's paradigm provided the theoretical foundation for this study. A sample of 560 university students was drawn from Quaid-i-Azam University Islamabad. The sample was drawn using stratified random sampling technique. Data were collected using Existence Scale, Warwick-Edinburg Mental Well-Being Scale, and Stress Scale. Results of linear regression analysis reveals that high perception of meaning in life will lead to high psychological well-being and low stress among university students. Non-significant differences are found on meaning in life variable with regard to gender in the sample using t-test. Together these results suggest that meaning in life independent of gender, is a significant predictor of the levels of stress and psychological well-being being directly related to psychological well-being and inversely related to stress levels.

Keywords: existential meaning in life, psychological well-being, stress, students

Procedia PDF Downloads 514